1. Technical Field
The disclosure relates generally to distance evaluation, and, more particularly to distance evaluation apparatuses and methods for evaluating distances from an observation point to objects in a scene using computer vision, image processing and optic techniques.
2. Background
The need to evaluate distances is a main concern for several fields, such as autonomous robotic navigation, depth map creation, human/machine interaction, surveillance and auto-focus systems used in imaging technology.
Conventionally, there are several methods for measuring distances which can be distinguished by the type, active or passive, of the device which utilize the methods. RADAR (RAdio Detection and Ranging) and LIDAR (LIght Detection and Ranging) methods are active devices and methods based on measuring the flight time of electromagnetic waves (radio or light wave) to and from same or different locations to measure distances. Additionally, other active distance measuring methods may utilize the flight time of ultrasonic waves, such as an ultrasonic range-finder. Active distance measuring systems based on light emission (e.g. LIDAR) offer a high degree of precision, however, they are often cumbersome and costly.
Passive distance measuring methods gather surrounding relevant information, often in the form of light waves, and do not emit any signal. Some passive distance measuring methods utilize triangulation techniques from stereoscopic cameras or an arbitrary number of cameras higher than two to create a depth map, containing distance information from a given observation point. Additionally, several passive distance measuring methods have also been proposed which evaluate distances by using several images of a given scene using different camera parameters. Some passive distance measuring systems are based on depth from defocus or depth from focus techniques. They rely on one or a plurality of captured images to evaluate distances. However, when several images must be acquired, the lengthy time required for the capture hinders real time applications, and such system would not be usable for objects and subjects in movement.
It is a subject of the present disclosure to palliate the disadvantages of the previous systems and describe methods and systems allowing distance evaluation for several objects in a scene from a single captured image.